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Science

Research Coordinator

Based on 10 assessments · 1 from real users

37% Moderate risk

Average realistic automation risk across all Research Coordinator profiles in the dataset.

Raw potential
67%
Realistic risk
37%

Raw potential = I/O automation ceiling. Realistic risk = adjusted for informal knowledge and social context.

Distribution across 10 profiles. Middle half of Research Coordinators score between 34% and 38%.

0% 50% 100%
p10 · 34%
45% · p90
On-screen work 49%

Done entirely on a computer. High AI exposure — these tasks are already in the automation zone.

In-person + screen 37%

Physical sensing, digital output — e.g. interviewing someone then writing a report. Partially protected.

Computer + action 13%

Computer input, real-world output — needs someone to act on it, not just software.

Fully in-person 1%

No computer required. Furthest from automation — the strongest human advantage.

3 synthetic profiles for a Research Coordinator, ordered by automation exposure. Tab between them to see how task mix drives the score difference.

Task Time Type Exposure
Training new lab staff or student volunteers on standard procedures and safety protocols
deep expertise social element
25% DA 0%
Literature review and database searching (PubMed, Web of Science, institutional repositories)
18% DD 62%
Coordinating IRB submissions, permits, and regulatory documentation with external agencies
deep expertise social element
16% AD 22%
Preparing lab supplies inventory, ordering equipment, managing budgets and purchase orders
14% DD 55%
Recruiting and scheduling study participants, managing consent forms and eligibility screening
deep expertise
11% AD 13%
Organizing meetings, tracking deadlines, maintaining project timelines and regulatory compliance checklists
6% DD 74%
Writing protocol summaries, progress reports, grant updates for PIs and funding bodies
deep expertise social element
5% DD 22%
Data entry and management (entering lab results, survey responses into databases; quality checking)
2% AD 43%

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